Driving Behavior Modeling Using Autoregressive Input-Output Hidden Markov Models

Abstract

This paper presents a driving behavior modeling method using autoregressive input-output hidden Markov models (AIOHMMs). First, model parameter learning and discrimination ways using the AIOHMMs are detailed. In experiments, we model four driving maneuvers with driver’s eye-gaze and ego-vehicle localization information and compare maneuver discrimination performances by four types of HMMs. Additionally, we discuss modeling performance by the AIOHMMs through the experiments.